SOT
Society of Toxicology www.toxsci.oxfordjournals.org
OXFORD
High-Throughput Screening of Chemical Effects on Steroidogenesis Using H295R Human Adrenocortical Carcinoma Cells
Agnes L. Karmaus,* Colleen M. Toole,+ Dayne L. Filer,* Kenneth C. Lewis, and Matthew T. Martin*,1
*National Center for Computational Toxicology, US EPA, Research Triangle Park, North Carolina; +Cyprotex (Formerly CeeTox, Inc.), Kalamazoo, Michigan; and +OpAns, LLC, Durham, North Carolina
1To whom correspondence should be addressed at National Center for Computational Toxicology, US EPA, 109 T.W Alexander Drive, Mail Drop D143-02, Research Triangle Park, NC 27711. Fax. 919-541-1194. E-mail: martin.matt@epa.gov.
Disclaimer: The United States Environmental Protection Agency (U.S. EPA) through its Office of Research and Development has subjected this article to Agency administrative review and approved it for publication. Mention of trade names or commercial products does not constitute endorsement for use. The views expressed in this article are those of the authors and do not necessarily represent the views or policies of the US EPA.
ABSTRACT
Disruption of steroidogenesis by environmental chemicals can result in altered hormone levels causing adverse reproductive and developmental effects. A high-throughput assay using H295R human adrenocortical carcinoma cells was used to evaluate the effect of 2060 chemical samples on steroidogenesis via high-performance liquid chromatography followed by tandem mass spectrometry quantification of 10 steroid hormones, including progestagens, glucocorticoids, androgens, and estrogens. The study employed a 3 stage screening strategy. The first stage established the maximum tolerated concentration (MTC; ≥ 70% viability) per sample. The second stage quantified changes in hormone levels at the MTC whereas the third stage performed concentration-response (CR) on a subset of samples. At all stages, cells were prestimulated with 10 uM forskolin for 48 h to induce steroidogenesis followed by chemical treatment for 48 h. Of the 2060 chemical samples evaluated, 524 samples were selected for 6-point CR screening, based in part on significantly altering at least 4 hormones at the MTC. CR screening identified 232 chemical samples with concentration-dependent effects on 17ß-estradiol and/or testosterone, with 411 chemical samples showing an effect on at least one hormone across the steroidogenesis pathway. Clustering of the concentration-dependent chemical-mediated steroid hormone effects grouped chemical samples into 5 distinct profiles generally representing putative mechanisms of action, including CYP17A1 and HSD3B inhibition. A distinct pattern was observed between imidazole and triazole fungicides suggesting potentially distinct mechanisms of action. From a chemical testing and prioritization perspective, this assay platform provides a robust model for high-throughput screening of chemicals for effects on steroidogenesis.
Key words: steroidogenesis; H295R cells; ToxCast; high-throughput screening.
Identifying potential endocrine disrupting compounds (EDCs) and understanding their mode of action is of high priority for chemical safety and regulatory agencies. The World Health Organization defines an endocrine disruptor as, “an exogenous substance or mixture that alters function(s) of the endocrine
system and consequently causes adverse health effects in an intact organism or its progeny or (sub)populations” (WHO/ UNEP, 2013). EDCs have been associated with adverse reproduc- tive and developmental effects as well as increased risk of hor- mone-dependent cancers (Yeung et al., 2011).
Most EDC research has largely focused on chemical interac- tion with hormone nuclear receptors, mainly estrogen and an- drogen receptors, and cellular signaling pathways for these receptors. For example, the ToxCast high-throughput screening program includes 18 unique assays that evaluate chemical in- teractions across the estrogen signaling pathway focusing on estrogen receptor binding and activation as well as downstream effects on cell proliferation (Judson et al., 2015) . However, inde- pendent of receptor activity, dysregulation, or interference with steroid hormone biosynthesis and metabolism (ie, steroidogen- esis) can alter steroid hormone levels contributing to endocrine disruption and ultimately result in impaired reproductive and sexual development (Sanderson, 2006; Whitehead and Rice, 2006; Ye et al., 2014). Altered hormone levels contributing to en- docrine disruption is not unique to steroid hormones; for exam- ple, mechanisms other than alterations in receptor occupancy have been known in thyroid hormone-related endocrine disrup- tion (Capen and Martin, 1989).
Given their key role in the formation of endogenous steroid hormones, enzymes involved in steroidogenesis are considered important targets for endocrine disrupting chemicals. However, the development of in vitro steroidogenesis assays has been a challenge because only adrenal and gonadal cells express ap- preciable cytochrome P450 side chain cleavage enzyme (CYP11A1), the initial enzyme in the steroid metabolism path- way required to commit cholesterol to a steroid hormone fate by forming pregnenolone (PREG) from cholesterol (Payne and Hales, 2004). CYP11A1 is expressed in the zona glomerulosa of the adrenal gland, Leydig cells of the testes, and theca cells of the ovary. Subsequent enzymes involved in steroidogenesis, in- cluding CYP17A1 and CYP19A1, are expressed in a variety of tis- sues including the liver, skin, and the nervous system (Payne and Hales, 2004). To date, no steroidogenically competent in vitro platform has been developed from ovarian cells. Several cell lines have been established from rodent Leydig cells, in- cluding R2C, mLTC, and BLTK1 cells for the evaluation of pro- gestagen and androgen levels (Ascoli, 1981; Forgacs et al., 2012; Rebois, 1982; Shin et al., 1968). The only human-derived, steroi- dogenically competent cell line is the human adrenocortical H295R cells (Gracia et al., 2006). The EPA’s Endocrine Disruptor Screening Program (EDSP) has incorporated the OECD validated H295R-based in vitro steroidogenesis assay (Test Guideline 456, OECD, 2011) as part of the Tier 1 screening battery (USEPA, 2006). The current design of the assay measures concentration- dependent changes in 17ß-estradiol and testosterone levels upon chemical treatment in a 24-well plate format (OECD, 2011). Given the need to screen large numbers of chemicals for po- tential endocrine disruption, and specifically for effects on steroidogenesis, the development of a high-throughput ste- roidogenesis assay to complement the high-throughput nuclear receptor assays is required.
In this study, we modified the existing OECD H295R in vitro steroidogenesis assay to perform high-throughput measure- ment of 13 hormones in 96-well format using a novel high- throughput HPLC-MS/MS (high-performance liquid chromatog- raphy followed by tandem mass spectrometry) method. This approach provides the ability to quantitatively assess changes in 4 hormone classes including glucocorticoids, progestagens, androgens, and estrogens. The assay was used to screen 2060 chemical samples in single concentration format. Those sam- ples having significant effects on at least 4 hormones were sub- sequently evaluated in concentration-response (CR). Comprehensively evaluating a panel of hormones across the steroidogenesis pathway allowed for the identification of
different putative mechanisms of action for chemicals. The data not only offered unique insights into the effects of a di- verse library of chemicals on hormone biosynthesis and metab- olism thereby complementing current EDC screening assays, but also demonstrate a novel use for H295R cells as a high- throughput and multiplexed screening platform for the disrup- tion of steroidogenesis.
MATERIALS AND METHODS
Chemical library
The chemical library used for this study contained 2060 samples representing 1998 unique test chemicals (Supplementary Table 1). Chemicals were selected from multiple ToxCast chemical lists established based on solubility in DMSO, commercial avail- ability, and affordability of the compound. The chemical inven- tory for this study included the ToxCast Phase I, Phase II, as well as a selection of Phase III chemicals. Phase I was largely com- posed of conventional pesticide actives whereas Phases II and III generally encompassed environmental chemicals of interest. In addition, the E1K chemical library, a set of roughly 800 chemi- cals enriched for endocrine active chemicals, was included. Information on the complete ToxCast chemical library is pub- licly available for download (http://www.epa.gov/ncct/dsstox/). A top nominal stock concentration of 100mM was attempted, solubility permitting, for the entire library.
Cell culture and treatment
All cell culture and treatment procedures were carried out at CeeTox, Inc (Kalamazoo, Michigan). Cell culture conditions and media preparation were conducted in accordance with the OECD Test No. 456 guidelines (OECD, 2011), with minor modifi- cations. Briefly, H295R cells (ATCC CRL-2128) were expanded for 5 passages and frozen in batches in liquid nitrogen. Prior to con- ducting steroidogenesis evaluation, batches of H295R cells were thawed and passed at least 4 times. The maximum passage number used for steroidogenesis evaluation was 10. Cells were maintained in a 1:1 mixture of Dulbecco’s Modified Eagle’s Medium with Ham’s F-12 Nutrient mixture (DMEM/F12) supple- mented with 5ml/1 ITS+ Premix (BD Bioscience) and 12.5 ml/L Nu-Serum (BD Bioscience). After seeding cells at 50%-60% conflu- ency into 96-well plates, an overnight acclimation period was al- lowed for cell adherence. Subsequently culture medium was replaced with 175 ul media containing 10 uM forskolin (FOR) to stimulate steroidogenesis for 48 h. Finally, the FOR stimulus me- dia was replaced, this time test chemical was added to a final concentration of 0.1% DMSO. Duplicates were included for all chemical treatments as well as controls [10 µM FOR and 3 uM pro- chloraz (PRO)] in addition to 4 DMSO solvent controls on each 96-well plate. Following 48 h of chemical treatment, media was removed, split into 2 vials of approximately 75 ul media each, and stored at -80℃ prior to steroid hormone quantification.
MTT cytotoxicity assay
Cell viability was evaluated by MTT cytotoxicity assay after chemical treatment in all studies. Briefly, after chemical expo- sure and removal of media, 500 ul of 0.5 mg/ml 3-[4,5-dime- thylthiazol-2-y]2,5-diphenyltetrazoliumbromide (MTT) solution was added to the cells remaining in the 96-well treatment plates. Following a 4h incubation at 37℃ and 5% CO2 to allow formazan-MTT crystal formation, the MTT solution was re- moved and blue formazan salt crystals were solubilized using
500 ul anhydrous isopropanol with shaking for 20 min. Absorbance at 570 and 650 nm were measured using a Packard Fusion plate reader. Background correction of absorbance units was used to determine percent change relative to controls. All plates contained multiple control wells including 10 uM FOR (n = 4; control for stimulation of steroidogenesis), 3 uM PRO (n=4; control for the inhibition of steroidogenesis), and digito- nin (n =4; control for cell death).
Initially, cytotoxicity was used to establish a maximum tol- erated concentration (MTC) per chemical sample whereby the ToxCast chemicals were evaluated at a maximum nominal con- centration of 100 uM, where possible. A target cell viability ≥70% was sought. Chemicals resulting in H295R cell viability of 20%-70% were diluted 10-fold, whereas those with < 20% viabil- ity were diluted 100-fold and re-evaluated. Dilutions were made until ≥ 70% viability was achieved for all chemicals establishing the MTC. The 70% cutoff criteria was established based on 5 times the baseline median absolute deviation (5 x BMAD), which uses the estimated baseline noise level of the assay to in- form on significant changes in cell viability. For the MTT data analysis, BMAD was defined as the median absolute deviation (MAD) of all chemical samples evaluated during MTC determi- nation, resulting in a BMAD of 6%; hence with a 5 x BMAD cutoff the allowable viability loss was set as 30%. MTT cytotoxicity evaluation was also conducted for the duplicates of all concen- trations for chemicals tested in the CR studies (CR; 6-point CR established by 3-fold serial dilutions from the MTC). MTC and percent viability are summarized in Supplementary Table 1.
Quantification of steroid hormones
Media samples from treated cells were transported on dry ice to OpAns, LLC (Durham, North Carolina) where all subsequent ex- tractions and quantification were performed. Briefly, samples were thawed to room temperature prior to liquid-liquid extrac- tion. Steroid hormones were extracted from media samples us- ing methyl tert-butyl ether (MTBE). An extra derivatization with dansyl chloride was included for estrogen (estrone and estra- diol) detection only. Steroid hormones were separated and quantified using high-performance liquid chromatography fol- lowed by tandem mass spectrometry (HPLC-MS/MS). More spe- cifically, reverse phase C18 gradient elution with electrospray positive ionization was used followed by MS/MS detection. All data were acquired using MassHunter Workstation Acquisition version B03.01 (Agilent Technologies, Inc), and processed using MassHunter Quantitative Analysis for QQQ.
To support accurate quantification of samples, the linear dy- namic range was determined for each hormone analyte from 3 standards (Table 1). The lower limit of quantification (LLOQ) and upper limit of quantification (ULOQ) were established using a 7- point standard curve. Furthermore, precision and accuracy of the extraction and quantification methods were calculated as the percent relative standard deviation (%RSD) of the spiked stan- dards and percent spiked standard recovered, respectively. The goal was to achieve 100% accuracy (ie, recover all spiked-in stan- dard at quantification with minimal loss during run time) and good precision (ie, have %RSD <15% to ensure reproducibility [Abdel-Khalik et al., 2013; USFDA, 2001]). The data collected in the study were within the specified margins, confirming high quality.
Data processing and analysis
All data were analyzed in R (R 3.1.1; R Foundation for Statistical Computing). In the single concentration MTC screen, samples
were deemed to have a significant effect on hormone levels us- ing a cutoff of ≥ |1.5-fold change| over DMSO controls on a per plate basis. Analysis of the CR data was performed using the ToxCast pipeline package in R (tcpl; http://epa.gov/ncct/toxcast/ data.html). Briefly, all data were analyzed on a per sample basis for each hormone endpoint independently. Data were not ad- justed for cytotoxicity, all MTT cytotoxicity assay results are available in Supplementary Tables 1 and 2. CR data were fit us- ing 3 models: constant, hill, and gain-loss, the winning model was chosen as that having the lowest Akaike Information Criterion. Curve parameters from the winning model such as logAC50 (the log10 concentration in micromolar at which 50% of the maximum fold change was achieved; modl_ga) and the modeled top of the curve (modl_tp) were used to quantify po- tency and efficacy, respectively. A sample was identified as hav- ing a significant effect on a hormone if it was fit with one of the CR models and if the efficacy (ie, change in hormone levels) ex- ceeded a specified threshold defined by a cutoff of ≥ 6 times the BMAD (the MAD of all normalized response values at the lowest 2 tested concentrations across all samples). All data are avail- able through the ToxCast data download website (http://epa. gov/ncct/toxcast/data.html) and ToxCast Dashboard (http://ac tor.epa.gov/dashboard/). Supplementary files for all data are also included herein: stage II MTT results including the deter- mined MTC for each chemical (Supplementary Table 1), stage III MTT results (Supplementary Table 2), stage II MTC screening raw hormone data (Supplementary Table 3), stage II MTC screening hit calls (Supplementary Table 4), stage III CR evalua- tion raw hormone data (Supplementary Table 5), and stage III CR evaluation hormone data curve fitting and tcpl outputs (Supplementary Table 6). Finally, all data processing R scripts are also available as Supplementary File S7.
Correlation analyses between MTC screening and CR results were conducted using Pearson’s linear correlation per hormone analyte using the median log2-fold change of results from MTC treatment. This was possible due to the MTC having been evalu- ated in both the MTC screening and CR stages of the study. Robust Z-prime (Z’) and strictly standardized mean difference (SSMD) values were calculated per hormone using the median and MAD of the control wells (DMSO, PRO, or FOR, respectively) raw response values included on all plates. The median Z’ and SSMD values from across all treated plates (from all stages with hormone quantification), were reported for PRO and FOR inde- pendently to demonstrate the robustness of the assay under generally stimulatory and inhibitory conditions. Clustering of the CR hormone profiles was conducted at the chemical-level using the modeled top (modl_tp) multiplied by the signal direc- tion (ie, 1 for upregulation and -1 for downregulation). Chemical-level analyses, aggregating the 524 samples run in CR down to the 514 unique tested chemicals, were performed using the “tcpl” package’s “tcplSubsetChid” function. Figure genera- tion for K-means clustering, hierarchical clustering, and heat- map generation were all conducted using the “gplots” package in R. All scripts developed to perform the analyses in the study are available as Supplemental file S7.
RESULTS Assay Workflow and Summary
The high-throughput steroidogenesis assay involved 3 stages: I. establishing the MTC, II. Screening chemical samples at the MTC for effects on hormone levels, III. CR evaluation for select chemical samples (Figure 1). Initially, 2060 chemical samples
| Steroid Hormone | Short Name | LLOQ (ng/ml) | ULOQ (ng/ml) | Standard | Standards (ng/ml) | Precisionª (%) | Accuracyb (%) | |
|---|---|---|---|---|---|---|---|---|
| Glucocorticoid | 11-Deoxycortisol | 11DCORT | 5 | 1000 | [2H11]-11DCORT | 20, 50, 800 | 5.0 | 101.7 |
| Deoxycorticosterone | DOC | 0.5 | 100 | [2H8]-DOC | 4, 10, 160 | 3.7 | 99.9 | |
| Cortisol | CORTISOL | 0.5 | 100 | [2H4]-CORTISOL | 20, 50, 800 | 3.3 | 99.7 | |
| Corticosterone | CORTICO | 0.5 | 100 | [2H8]-CORTICO | 20, 50, 800 | 4.7 | 100.5 | |
| Progestagen | 17a-Hydroxyprogesterone | OHPROG | 0.2 | 40 | [2H8]-OHPROG | 4, 10, 160 | 4.0 | 99.6 |
| 17a-Hydroxypregnenolone | OHPREG | 5 | 1000 | [2H3]-OHPREG | 20, 50, 800 | 6.7 | 100 | |
| Progesterone | PROG | 0.2 | 40 | [2H9]-PROG | 4, 10, 160 | 3.3 | 98.1 | |
| Pregnenolone | PREG | 2 | 400 | [2H4]-PREG | 20, 50, 800 | 10.0 | 100.9 | |
| Androgen | Dehydroepiandrosterone | DHEA | 3 | 600 | [2H5]-DHEA | 20, 50, 800 | 4.0 | 100.1 |
| Androstenedione | ANDR | 1 | 200 | [2H5]-ANDRO | 4, 10, 160 | 4.7 | 99.9 | |
| Testosterone | TESTO | 0.1 | 20 | [2Hs]-TESTO | 0.4, 1, 16 | 5.7 | 100.7 | |
| Estrogen | Estrone | ESTRONE | 0.03 | 6 | [2H4]-ESTRO | 0.4, 1, 16 | 5.0 | 100.4 |
| Estradiol | ESTRADIOL | 0.03 | 6 | [2H5]-ESTRA | 0.4, 1, 16 | 6.3 | 101.4 |
ULOQ, upper limit of quantification
ªPrecision was calculated as the %RSD of the standards.
“Accuracy was calculated as the percent standard recovered.
Stage 1: MTC determination 2060 samples
Stage 2: MTC hormone screen 2060 samples
Stage 3: CR hormone evaluation 524 samples
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were evaluated for cytotoxicity to establish an MTC (ie, a single concentration with > 70% cell viability). In total, 1203 chemical samples had an MTC of 100 µM, 812 chemical samples had MTC between 1 and 99 uM, and 45 chemical samples had MTC less than 0.9 uM. In the MTC screen, all chemical samples were tested at their MTC for effects on steroidogenesis by quantifica- tion of 13 hormones (Table 1). Three hormones, PREG, dehydro- epiandrosterone, and corticosterone, consistently had data below the LLOQ and were not included in subsequent analyses. For MTC screening purposes, an absolute fold change cutoff of ≥ 1.5-fold (relative to DMSO controls on a per-plate basis) was used to identify chemical samples eliciting effects on hormone levels. In total, 955 chemical samples altered at least one hor- mone and 403 samples had effects on ≥ 4 hormones.
All 403 chemical samples identified using the criteria of ≥ 4 hormones altered at the MTC were included in the stage III CR evaluation. Additionally, 121 chemical samples not meeting this criteria were randomly chosen in order to evaluate the sen- sitivity of our selection criteria. As a result, 524 samples were evaluated in CR. Of the CR tested samples, a total of 411 chemi- cal samples had concentration-dependent effects on at least 1
hormone analyte. From these 411, 347 chemical samples had been selected based on the CR selection criteria, resulting in a selection sensitivity or recall of 86% when using the CR selection criteria. In contrast, only 64 of the additional 121 chemical sam- ples not meeting the CR selection criteria altered at least one hormone in stage III, a selection sensitivity of 53% (Supplementary Table 8 summarizes the selection sensitivity with different CR selection criteria). For each hormone, statisti- cally derived cutoff criteria were calculated based on 6 times BMAD (BMAD values were in log2 fold-change) allowing for a data-driven cutoff that directly reflects the relative baseline noise level for each endpoint. The resulting cutoffs ranged from 1.5-fold (BMAD of 0.097) for 11DCORT to a cutoff of 2-fold (BMAD of 0.17) for both ESTRADIOL and TESTO (Table 2).
Assay Performance Evaluation
Correlation analysis was conducted to evaluate the reproduc- ibility of the log2 fold-change achieved at the MTC concentra- tion between single concentration MTC screening and CR testing. Overall the squared Pearson’s correlation coefficient (r2) between the 2 phases of this study, which were conducted
| Hormone Short Name | Correlation of Maximum Fold Changeª | Z' (FOR)b | Z' (PRO)" | SSMD (FOR)ª | SSMD (PRO)e | BMADf | CR Cutoff (Fold-Change)& |
|---|---|---|---|---|---|---|---|
| 11DCORT | 0.82 | 0.76 | 0.88 | 15 | -27 | 0.097 | 1.50 |
| DOC | 0.45 | 0.65 | 0.51 | 10 | 7 | 0.154 | 1.90 |
| CORTISOL | 0.78 | 0.67 | 0.83 | 11 | -18 | 0.164 | 1.98 |
| PROG | 0.79 | 0 | 0.85 | 1 | 21 | 0.163 | 1.97 |
| OHPROG | 0.71 | 0.62 | 0 | 10 | -2 | 0.150 | 1.87 |
| OHPREG | 0.64 | 0.81 | 0.77 | 20 | 3 | 0.119 | 1.64 |
| ANDR | 0.81 | 0.68 | 0.84 | 11 | 19 | 0.127 | 1.70 |
| TESTO | 0.57 | 0.57 | 0.75 | 8 | -13 | 0.172 | 2.05 |
| ESTRONE | 0.65 | 0.79 | 0.76 | 18 | -14 | 0.135 | 1.75 |
| ESTRADIOL | 0.64 | 0.73 | 0.72 | 13 | -11 | 0.173 | 2.05 |
ªCorrelation of log2 fold-change was calculated by comparing maximum response achieved by the MTC tested in the MTC screening versus CR evaluation for 524 sam- ples. Values presented are r2 from Pearson correlations.
Median Z-prime across all tested plates using forskolin (FOR) as the control.
“Median Z-prime across all tested plates using prochloraz (PRO) as the control.
dMedian strictly standardized median difference (SSMD) across all tested plates using FOR as the control.
eMedian SSMD across all tested plates using PRO as the control.
‘Baseline median absolute deviation (BMAD; presented as log2 fold-change). 8CR cutoff shown as a fold-change equating to 6x BMAD.
independently, was on average 0.70 across all measured hor- mones (Table 2) suggesting good reproducibility. As another measure of assay performance, Z’ and SSMD values were calcu- lated using FOR and PRO as generally stimulatory and inhibitory controls, respectively (Table 2). Assay endpoints with Z’ values between 0.5 and 1 are considered to be excellent assays. Each measured hormone had a positive control with a Z’ > 0.5. Furthermore, SSMD was used to demonstrate overall assay quality and directionality. FOR generally increased hormone quantities with excellent dynamic range based on SSMD values ≥ 7, whereas PRO generally inhibited hormone production with excellent dynamic range based on SSMD values ≤-7. Specifically, FOR stimulated androgen and estrogen hormone production while PRO inhibited the production of these hor- mones consistently and robustly.
Comparison to OECD Guideline Study
This study presents a high-throughput modification of an OECD-validated assay. Although high-throughput screening as- says are not always amenable to traditional validation approaches, a performance-based approach was applied to help establish confidence in our identification of steroidogenesis dis- rupting chemicals. Among the 12 core chemicals included in the OECD H295R interlaboratory validation study (Hecker et al., 2011), the MTC screening dataset included 7 of the 12 core chemicals comprising FOR, PRO, atrazine, molinate, paraben, benomyl, and nonoxynol-9. The 5 core chemicals not included in our dataset were either not included in the ToxCast inventory or was a protein (human chorionic gonadotropin) and hence not in the scope of this study. MTC screening correctly identified the same effect as the OECD validation study with benomyl and nonoxynol-9 having no effect on any hormone and the others (FOR, PRO, atrazine, molinate, and paraben) eliciting increase/ decrease in ESTRADIOL and/or TESTO. Furthermore, 4 of these chemicals (FOR, PRO, atrazine, and molinate) were also evalu- ated in the CR stage, confirming the desired concentration- dependent effects on ESTRADIOL and/or TESTO. In addition to correctly identifying the effects of the core chemicals on the 2
endpoints included in the OECD guideline assay, our study iden- tified other hormones altered by these chemicals.
Profiling and Mechanism of Action Categorization
The nearly complete panel of hormones measured in this study provides a comprehensive evaluation of chemical effects on the steroid hormone biosynthesis and metabolism pathway. Distinguishing profiles of chemical-mediated changes in hor- mone levels can be useful for hypothesizing mechanisms of ac- tion for steroidogenesis disruption.
PRO, an imidazole fungicide, is the best characterized and most widely used reference chemical for steroidogenesis stud- ies. PRO potently inhibits the hydroxylase activity of CYP17A1 resulting in the inhibition of androgen production (Blystone et al., 2007). The CYP17A1 enzyme is responsible for 2 steps in the steroidogenesis pathway catalyzing both a hydroxylation and 17, 20-lyase reaction. In our study, PRO significantly altered the levels of 8 of the 10 hormones evaluated (Figure 2). More specifically, the levels of PROG and DOC, which precede CYP17A1 hydroxylase activity were increased relative to DMSO controls, while all hormones produced as products of CYP17A1 activity were significantly decreased or unchanged. All 8 hor- mones that were altered by PRO had AC50 values over a tight range of 0.1-0.3 uM. The consistency of the potency and profile of altered hormone levels supports the reported CYP17A1 mech- anism for PRO.
The current study included 18 conazoles evaluated in stage III CR, expanding upon the previous knowledge on the effects of conazoles on steroidogenesis. Previous studies have only inves- tigated select conazoles for effects on steroidogenesis, namely PRO, ketoconazole, and imazalil (Ulleras et al., 2008). The evalua- tion of these conazole fungicides effects on steroidogenesis re- veals that the 2 structurally distinguishable conazole classes, imidazole and triazole, can be approximately differentiated from one another based on their distinct profile of effects on steroidogenesis (Figure 3). With the exception of clotrimazole, the imidazoles cluster together due to increases in PROG and/or DOC in addition to strong decreases in COTRISOL, 11DCORT,
PREG
PROG
DOC
CORTICO
HSD3B1
CYP21A1
CYP11B1
AC50: 0.18 uM max response: 5.6-fold
AC50: 0.051 uM max response: 4.2-fold
CYP17A1
CYP17A1
OHPREG
OHPROG
11DCORT
CORTISOL
HSD3B1
CYP21A1
CYP11B1
AC50: 0.35 uM max response: - 1.8-fold
AC50: 0.3 uM max response: - 5-fold
CYP17A1
CYP17A1
DHEA
ANDR
TESTO
HSD3B1
HSD17B3
AC50: 0.17 uM max response: - 5.5-fold
AC50: 0.17 uM max response: - 4.8-fold
CYP19A1
CYP19A1
ESTRONE
ESTRADIOL
HSD17B3
AC50: 0.28 uM max response: - 6-fold
AC50: 0.12 uM max response: - 3-fold
ANDR, TESTO, ESTRONE, and ESTRADIOL. The triazole fungi- cides showed more diverse behavior with a generally conserved decrease in CORTISOL levels. Furthermore, most conazoles demonstrate consistent AC50 values across all hormones they concentration-dependently altered supporting the hypothesis that they have a single target mediating their primary effects on steroidogenesis.
To investigate the profiles of steroidogenic disruption K-means clustering was used to identify 5 distinct profiles (Figure 4; Supplementary Table 9 summarizes the identity of
chemicals per cluster). For this analysis, the 411 chemical sam- ples that elicited concentration-dependent effects on ≥ 1 hor- mone in stage III CR evaluation were mapped to 401 unique chemicals which were used as input for clustering. Cluster A is composed of 137 chemicals eliciting overall increases in hor- mone levels, most strongly driven by increases in PROG, OHPROG, ESTRONE, and ESTRADIOL. This first profile may be a result of chemical-mediated stimulation of steroidogenesis or chemical-mediated disruption of hormone metabolism/ turnover. For example, FOR, a chemical known to increase
0.58
0.33
0.39
Fenbuconazole
0.46
0.31
0.34
Difenoconazole
0.09
0.1
Metconazole
0.41
0.33
Diniconazole
5.59
Paclobutrazol
0.65
1.71
4.48
Triticonazole
0.93
0.56
5.28
1.63
3.78
2.93
8.76
8.7
Tebuconazole
0.38
0.35
0.28
Flusilazole
1.84
3.14
3.35
3.33
5
3.38
4.72
Cyproconazole
0.25
0.13
0.14
0.41
0.4
0.35
0.32
Imazalil
0.35
0.37
0.19
0.14
0.12
0.44
0.28
0.23
0.08
Triflumizole
0.18
0.05
0.3
0.35
0.17
0.17
0.28
0.12
Prochloraz
0.65
0.76
1
0.86
1.02
0.32
0.89
Ketoconazole
4.85
4.16
30.63
1.65
46.4
35.21
26.48
2.66
Myclobutanil
0.09
0.03
0.05
0.15
0.2
0.18
0.37
0.18
Clotrimazole
21.97
1.14
21.65
22.82
27.66
30.26
50.73
48.3
Triadimenol
13.16
4.94
17.25
20.56
51.51
37.5
30.14
44.19
18.3
Triadimefon
Color Key
1.85
1.86
3.59
7.66
4.12
1.38
1.89
1.28
Epoxiconazole
OHPREG
PROG
OHPROG
DOC
CORTISOL
11DCORT
ANDRO
TESTO
ESTRONE
ESTRADIOL
-6
-2
2
6
log2(fold change)
steroidogenesis across all hormones, can be found in Cluster A. Additionally, atrazine, a core chemical that the OECD validation study expected to weakly induce estrogen levels as a result of aromatase induction in vitro, was also in cluster A due to con- centration-dependent increases in ESTRADIOL. Cluster B con- tains 35 chemicals with PRO-like profiles constituting marked increases in PROG and DOC levels and decreases among andro- gens, the remaining glucocorticoids, and estrogens suggesting putative CYP17A1 disruption. Cluster C is composed of 50 chemicals with increased progestagen levels (OHPREG, OHPROG, and PROG) with simultaneous decreases across the rest of the hormones evaluated, which may result from HSD3B1 disruption. Finally, clusters D and E showed overall decreases in hormone levels with both clusters having consistent decreases in glucocorticoid and androgen levels. The clusters are distinguished from one another by estrogen responses. Cluster D, composed of 36 chemicals, consistently decreased estrogens suggesting overall inhibition of the ste- roidogenic pathway (ie, putative CYP11A1 inhibition, or chemi- cal-mediated effects upstream of steroidogenesis). In contrast, the 143 chemicals in cluster E have no change or increased estrogen levels overall.
DISCUSSION
In vitro evaluation of chemical-mediated disruption of estro- genic and androgenic activity has historically been focused on
nuclear receptor interactions. However, it is paramount that ef- fects on steroidogenesis are evaluated because changes in hor- mone levels can also result in adverse outcomes, independent of nuclear receptor binding. More specifically, disruption of ste- roidogenesis can result in reproductive and developmental tox- icity including nipple retention, decreases in anogenital distance, and fertility (Sanderson, 2006; Whitehead and Rice, 2006; Ye et al., 2014). In males, chemical-mediated decreases in androgen levels as a result of HSD3B inhibition, CYP17A1 inhibi- tion, or modulation of CYP19A1 activity have been associated with testicular dysgenesis syndrome and adverse reproductive effects (Edwards et al., 2006; Sharpe, 2006; Skakkebaek et al., 2001). For example, atrazine is an herbicide known to disrupt steroidogenesis and was one of the core chemicals in the OECD interlaboratory validation studies eliciting concentration- dependent effects on both TESTO and ESTRADIOL. Atrazine- mediated adverse reproductive effects in rodents have been at- tributed to the disruption of steroidogenesis in light of the fact that it does not interact with nuclear receptors (Connor et al., 1996; Forgacs et al., 2013; Roberge et al., 2004; Trentacoste et al., 2001), which was also confirmed in ToxCast assays where it does not result in any effects in AR or ER assays. Similarly, the fungicide PRO has in vivo anti-androgenic effects across species including fish, rodents, and frogs as a result of CYP17A1 inhibi- tion which disrupts steroidogenesis leading to adverse effects on sexual development (Ankley and Gray, 2013; Blystone et al., 2007; Vinggaard et al., 2005).
A
B
C
D
E
Color Key
-6
-2
2
6
log2(fold change)
OHPREG
PROG
OHPROG
DOC
CORTISOL
11DCORT
ANDRO
TESTO
ESTRONE
ESTRADIOL
Despite the well-characterized effects of a few prototype chemicals, very few others have been comprehensively evalu- ated for effects on steroidogenesis, much less characterized for mechanisms of action underlying these effects. The conazoles fungicides PRO, ketoconazole, and imazalil have been previ- ously investigated and characterized as CYP17A1 inhibitors con- firming results from the profiling approach herein (Blystone et al., 2007; Loose et al., 1983; Ohlsson et al., 2010; Ulleras et al., 2008); however, this study is the first to expand beyond small prototypical chemical sets and comprehensively evaluate the effects of a large library of structurally diverse chemicals across the steroid hormone biosynthetic pathway. The chemical in- ventory studied herein included multiple libraries from the ToxCast high-throughput screening program and was not a ran- dom selection of chemicals, but rather it was enriched for po- tentially endocrine-active chemicals. The OECD validated H295R steroidogenesis assay (OECD Test Guideline 456) was adapted to high-throughput and a novel HPLC-MS/MS approach was used to successfully quantify 10 hormone analytes. Efforts to apply metabolomics and/or quantify a larger panel of
hormones using mass spectrometry in H295R cells have been attempted in the past (Abdel-Khalik et al., 2013; Jeanneret et al., 2015; Kang et al., 2013; Nielsen et al., 2012; Rijk et al., 2012; Ulleras et al., 2008); however, these studies also deviated from the OECD assay guideline and the current study is the first to apply this approach successfully on such a large scale. Our methodology was robust with high Z’ and SSMD values and good reproduc- ibility across the MTC and CR stages of the study. The use of HPLC-MS/MS for quantification of the steroid hormones im- proved accuracy, throughput, and allowed lower detection lim- its compared to the traditional ELISA or RIA previously used in hormone studies. Furthermore, despite adaptation to high- throughput, inclusion of a FOR prestimulus, and use of a novel quantification method, our study design was able to correctly identify the chemical effects on steroidogenesis when bench- marking against the OECD guideline study. Notably, the high- throughput method herein not only correctly identified antici- pated effects on ESTRADIOL and/or TESTO, but also provided in- sight on other hormone endpoints across the steroidogenesis pathway. It is important to note that the current study design
was modified from the OECD guideline: all test samples were evaluated in duplicate rather than triplicate; 70% cell viability was accepted instead of 80%; FOR prestimulus was included to enable robust dynamic responses in both up- and downregula- tion of hormone levels; and concentration-dependent effects were evaluated using the ToxCast Data Analysis Pipeline rather than the OECD guideline recommended Dunnett’s Test to iden- tify significant effects in consecutive chemical concentration groups. However, the added value of having quantified effects on 10 hormones rather than simply ESTRADIOL and/or TESTO allowed for the profiling of chemical-elicited disruption of ste- roidogenesis to help in hypothesis generation for putative mechanisms of action. Yet the capacity to use this assay for chemical safety decisions warrants further evaluation and study, including the detailed evaluation of selection criteria, in vivo relevance especially as it pertains to the profile of hor- mone changes, and integration of other relevant assays (eg, aro- matase inhibition assays).
The 3 stage approach sought to establish an MTC to mini- mize any confounding effects of cytotoxicity, while selection of chemicals from stage II to stage III aimed to hone in on identify- ing chemical-mediated effects on steroidogenesis. The number of chemicals identified as having effects on hormone levels is not altogether surprising as the chemical inventory was se- lected in part based on potential endocrine-activity, and our se- lection criteria were intended to be inclusive for screening purposes to minimize false negatives. Additionally, the current screening effort profiles a larger portion of the steroidogenic pathway than ever before (ie. 10 hormones quantified rather than ESTRADIOL and TESTO only), inherently resulting in a larger number of chemicals having any effect on hormone lev- els as additional mechanisms of action can be detected. However, it is also important to note that chemicals not se- lected for CR evaluation should not be considered as inactive for disruption of steroidogenesis as the selection process was based on a combination of activity in MTC screen and overall testing efficiency. Given the number of hormones measured, the repro- ducibility across studies, and the distinct profiles observed, our results suggest that it is unlikely that chemicals not selected for the CR stage have a significant effect on steroidogenesis. Yet re- fining the chemical selection criteria, which herein simply re- quired effects on ≥ 4 hormones in the MTC screening, may identify chemicals that should be tested in CR. Additional fol- low-up studies are required to investigate the potential for highly targeted hormone effects (eg, chemicals altering estrogen levels exclusively), which may have an impact on future chemi- cal selection for CR follow-up.
The quantification of hormones across the steroidogenesis pathway in CR across a diversity of chemicals enabled a com- prehensive profiling of chemical effects that can support hy- pothesis generation for putative mechanisms of steroidogenesis perturbation. More specifically, the evaluation of conazole fungicides revealed distinguishable profiles of hor- mone effects for triazole versus imidazole conazoles illustrating the influence of chemical structure on bioactivity. Furthermore, the profiling results highlight a multitude of possible targets that can result in different effects on hormone levels evident in 401 out of the 514 chemicals that elicited concentration-depen- dent effects on at least one hormone. For example, increased progestagen levels in coordination with decreased androgen and estrogen levels were observed with CYP17A1 inhibition by PRO. Other observed profiles included the decrease of androgen levels with concurrent increases in estrogens suggesting in- creased aromatase (CYP19A1) activity or decreased estrogen
turnover by sulfotransferases. Future studies will seek to char- acterize the profiles identified, to screen additional chemicals in CR, and to develop in silico predictive models to identify chemi- cals targeting steroidogenesis.
The H295R high-throughput screening assay presented herein fills a critical gap in the ability to evaluate large chemical libraries for effects on steroidogenesis in vitro. This assay also complements the existing EPA EDSP Tier 1 testing battery which has included the evaluation of < 100 chemicals effects on ste- roidogenesis using 2 in vitro assays: the OECD validated H295R assay only evaluating TESTO and ESTRADIOL levels (ie, OCSPP 890.1550) and the CYP19A1 inhibition assay (ie, OCSPP 890.1200). The novel approach outlined in this study to quantify a majority of hormones in the steroidogenesis pathway in high-through- put provides insight into the unique profiles elicited by different mechanisms of action aiding hypothesis generation, and ulti- mately serving as the basis for models that can support chemi- cal testing prioritization.
FUNDING
A.L.K. and D.L.F. were supported by appointments to the Research Participation Program of the U.S. Environmental Protection Agency, Office of Research and Development, ad- ministered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and the U.S. EPA.
ACKNOWLEDGMENTS
The authors would like to thank Dr Richard Judson, Sine Rosenberg, Dr Kevin Crofton, and Dr Russell Thomas for the critical reading of the manuscript, as well as the ToxCast scientists for many helpful discussions.
SUPPLEMENTARY DATA
Supplementary data are available online at http://toxsci. oxfordjournals.org/.
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